Thermal and Electrical Parameter Identification of a Proton Exchange Membrane Fuel Cell Using Genetic Algorithm

Autor: Ángel Navarro-Pérez, H. Eduardo Ariza, E. García, A. Correcher, Carlos Sánchez
Jazyk: angličtina
Rok vydání: 2018
Předmět:
Work (thermodynamics)
Identification
Materials science
Control and Optimization
Computer science
020209 energy
Energy Engineering and Power Technology
Proton exchange membrane fuel cell
02 engineering and technology
Fault (power engineering)
lcsh:Technology
Automotive engineering
TECNOLOGIA ELECTRONICA
Thermal
Genetic algorithm
0202 electrical engineering
electronic engineering
information engineering
genetic algorithm
LabVIEW
Electrical and Electronic Engineering
Engineering (miscellaneous)
Physical model
model
Renewable Energy
Sustainability and the Environment
lcsh:T
Condition monitoring
INGENIERIA DE SISTEMAS Y AUTOMATICA
Identification (information)
PEM fuel cell
electrical_electronic_engineering
Scalability
INGENIERIA ELECTRICA
identification
Biological system
Energy (signal processing)
Energy (miscellaneous)
Model
Zdroj: Energies
Volume 11
Issue 8
Energies, Vol 11, Iss 8, p 2099 (2018)
RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
instname
ISSN: 1996-1073
DOI: 10.3390/en11082099
Popis: [EN] Proton Exchange Membrane Fuel Cell (PEMFC) fuel cells is a technology successfully used in the production of energy from hydrogen, allowing the use of hydrogen as an energy vector. It is scalable for stationary and mobile applications. However, the technology demands more research. An important research topic is fault diagnosis and condition monitoring to improve the life and the efficiency and to reduce the operation costs of PEMFC devices. Consequently, there is a need of physical models that allow deep analysis. These models must be accurate enough to represent the PEMFC behavior and to allow the identification of different internal signals of a PEM fuel cell. This work presents a PEM fuel cell model that uses the output temperature in a closed loop, so it can represent the thermal and the electrical behavior. The model is used to represent a Nexa Ballard 1.2 kW fuel cell; therefore, it is necessary to fit the coefficients to represent the real behavior. Five optimization algorithms were tested to fit the model, three of them taken from literature and two proposed in this work. Finally, the model with the identified parameters was validated with real data.
This research was funded by COLCIENCIAS (Administrative department of science, technology and innovation of Colombia) scholarship program PDBCEx, COLDOC 586, and the support provided by the Corporacion Universitaria Comfacauca, Popayan-Colombia
Databáze: OpenAIRE
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